Computational Sprinting: Exceeding Sustainable Power in Thermally Constrained Systems

Although process technology trends predict that transistor sizes will continue to shrink for a few more generations, voltage scaling has stalled and thus future chips are projected to be increasingly more power hungry than previous generations. Particularly in mobile devices which are severely cooling constrained, it is estimated that the peak operation of a future chip could generate heat ten times faster than than the device can sustainably vent. However, many mobile applications do not demand sustained performance; rather they comprise short bursts of computation in response to sporadic user activity. To improve responsiveness for such applications, this dissertation proposes computational sprinting, in which a system greatly exceeds sustainable power margins (by up to 10Ã?) to provide up to a few seconds of high-performance computation when a user interacts with the device. Computational sprinting exploits the material property of thermal capacitance to temporarily store the excess heat generated when sprinting. After sprinting, the chip returns to sustainable power levels and dissipates the stored heat when the system is idle. This dissertation: (i) broadly analyzes thermal, electrical, hardware, and software considerations to analyze the feasibility of engineering a system which can provide the responsiveness of a plat- form with 10Ã? higher sustainable power within today\u27s cooling constraints, (ii) leverages existing sources of thermal capacitance to demonstrate sprinting on a real system today, and (iii) identifies the energy-performance characteristics of sprinting operation to determine runtime sprint pacing policies

Thermal Energy Storage for Datacenters with Phase Change Materials

Datacenters, vast warehouses containing millions of servers that run the internet and the cloud, have experienced double digit growth for almost two decades. Datacenters cost hundreds of millions of dollars, with the largest now exceeding over a billion dollars each, and consume enormous amounts of power–over 2% of all electricity in the US and projected to increase up to 10% by 2030. The impact of such high compute density, with thousands of individual compute nodes packed together in a small space, is heat: every watt of power used by servers must be removed form the datacenter. This requires active cooling: air cooling is by far the most common with an air conditioner or other form of heat exchanger cooling air in the datacenter room then transporting heat outside the facility to heat exchanger or similar fixture. Such a system is simple, common, and functional, but inherently inefficient due to the nature of datacenter workloads. Datacenters primarily server user facing workloads, that is: the user requests a search or sends and email and their query prompts load in the datacenter. The query is handled locally, on a relative geographic scale, to provide a low response time and positive user experience. This necessitates globally distributed datacenter capacity, but also creates a diurnal load pattern whereby datacenters are most heavily loaded during the peak hours when users in their region of service are awake and active online versus the off hours when users are offline or asleep and query requests are low. Because datacenter infrastructure must be provisioned for peak load, servers, power distribution, and cooling infrastructure is significantly underutilized most of the time. This dissertation investigates the cooling needs of datacenters, and proposes to decouple the work and cooling needs. Specifically, we hypothesize that by storing thermal energy we can reshape the thermal profile of a datacenter to better balance cooling load throughout the day. We call this technique Thermal Time Shifting (TTS). First, we discuss how phase change materials (PCMs) enable TTS and evaluate the potential use scenarios of placing a small amount of PCM inside of servers for thermal energy storage. Next we dive deeper into the potential of thermal energy storage and propose Virtual Melting Temperatures (VMT), a technique that uses active job placement to control the melting and cooling of PCM to enable a much greater degree of control over the behavior of the thermal profile. Finally we propose and evaluate Thermal Gradient Transfer (TGT), a technique that uses direct water cooling to move heat straight from CPUs and GPUs to the wax for wider applicability and greater peak cooling load reduction.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/147726/1/skachm_1.pdfDescription of skachm_1.pdf : Restricted to UM users only

Fish under pressure: examining behavioural responses of Iberian barbel under simulated hydropeaking with instream structures

Research ArticleHydropeaking is the rapid change in the water flow downstream of a hydropower plant, driven by changes in daily electricity demand. These fluctuations may produce negative effects in freshwater fish. To minimize these impacts, previous studies have proposed habitat enhancement structures as potential mitigation measures for salmonids. However, the recommendation of these mitigation measures for cyprinids remains scarce and their effects unknown. In this study, the effects of potential habitat mitigation structures under simulated hydropeaking and base-flow conditions are examined for Iberian barbel (Luciobarbus bocagei) in an indoor flume. Solid triangular pyramids and v-shaped structures were evaluated as potential flow-refuging areas and compared with a configuration without structures. A novel, interdisciplinary approach is applied to investigate individual and group responses to rapidly changing flows, by assessing physiological (glucose and lactate), movement behaviour (structure use, sprints and drifts) and the pressure distribution using a fish-inspired artificial lateral line flow sensor. The major findings of this study are four-fold: 1) Under hydropeaking conditions, the v-shaped structures triggered a lactate response and stimulated individual structure use, whereas solid structures did not elicit physiological adjustments and favoured individual and group structure use. Overall, both solid structures and their absence stimulated sprints and drifts. 2) The hydrodynamic conditions created in hydropeaking did not always reflect increased physiological responses or swimming activity. 3) Each event-structure combination resulted in unique hydrodynamic conditions which were reflected in the different fish responses. 4) The most relevant flow variable measured was the pressure asymmetry, which is caused by the vortex size and shedding frequency of the structures. Considering the non-uniform nature of hydropeaking events, and the observation that the fish responded differently to specific flow event-structure combinations, a diverse set of instream structures should be considered for habitat-based hydropeaking mitigation measures for Iberian barbelinfo:eu-repo/semantics/publishedVersio

Effects of hydropeaking and refuge configurations on the behaviour of cyprinids in experimental flume conditions

Doutoramento em Restauro e Gestão Fluviais (FLUVIO) - Instituto Superior de Agronomia / Faculdade de Arquitetura / Instituto Superior TécnicoFlow regime regulates the ecological integrity of river ecosystems, shaping the structure and function of fish communities. The discharge fluctuations in hydropower plants in response to peak electricity demand (i.e. hydropeaking) result in rapid flow changes in tailwaters. The continued hydropower operations produced morphological, hydraulic and water quality alterations, affecting downstream fish. Fish responses to hydropeaking range from organism to life-cycle event changes. It is challenging to establish a cause-effect relationship between flow variability and a fish response, and to propose adequate mitigation measures. In the first part of this research, a literature review was conducted to find evidence for that relationship. The review showed that flow variability can represent a stressor for fish. However, it remained unclear if the responses were maladaptive. In the second part, the effects of hydropeaking and refuges were assessed for L. bocagei in an indoor flume. A multidisciplinary approach was adopted, where fish responses were combined with a hydraulic characterization. Peak events were tested by manipulating magnitude, peak frequency and duration. The refuges were lateral (meandering and one-sided deflectors) and instream (triangular pyramids and v-shaped) structures, tested along three experimental campaigns. Glucose and lactate (secondary responses), and movement behaviour (whole-animal responses) were assessed. The flow field and fluid-body interactions were characterized by using acoustic Doppler velocimetry and an artificial lateral line probe respectively. The movement patterns of L. bocagei were diverse and not always proportional to the severity of the flow event. Lateral deflectors and v-shaped structures provided low velocity areas. However, the created flow complexity represented an additional constraint for fish, reducing their ability to find them. Flow thresholds that represented the resting state of L. bocagei were identified, and specific movement patterns were related with hydrodynamic changes. Practical recommendations for operational schemes and for the implementation of mitigation measures to hydropeaking were proposedN/

Palm biomass supply management : a predictive analysis tool

The flourishing of oil palm industry has always been regarded as a double-edged sword. While it has significantly contributed to the economic growth, it is, nonetheless, disputably unsustainable as it is a land-intensive industry and causing disposal problems by leaving behind massive waste. To strengthening the industry’s competitive advantage and offsetting its drawbacks, this thesis presents a forward-looking framework – Biomass Supply Value Chain (BSVC)– to put emphasis on the value creation for the biomass industry. It aims to enhance the current biomass supply chain by harnessing the emerging technological advancement of artificial intelligence (AI), as well as by incorporating game theory to examine the strategic arrangement of the industry players. The proposed framework is capable of optimising the procurement process in the supply chain management: first, by identifying biomass properties for optimum biomass utilisation through the developed Biomass Characteristic Index (BCI); second, by applying AI into supply chain-related tasks for aiding better decision-making and problem-solving; and third, by adopting game theory in analysing strategic options, and providing appropriate strategies to minimise uncertainty and risk in procurement process. The “value” as suggested in the BSVC does not merely refer to a narrow economic sense, but is an all-encompassing value concerning non-monetary utility values, including sustainability, environmental preservation and the appreciation of the biomass industry

Forecasting and Assessing Risk of Individual Electricity Peaks

Introduction The overarching aim of this open access book is to present self-contained theory and algorithms for investigation and prediction of electric demand peaks. A cross-section of popular demand forecasting algorithms from statistics, machine learning and mathematics is presented, followed by extreme value theory techniques with examples. In order to achieve carbon targets, good forecasts of peaks are essential. For instance, shifting demand or charging battery depends on correct demand predictions in time. Majority of forecasting algorithms historically were focused on average load prediction. In order to model the peaks, methods from extreme value theory are applied. This allows us to study extremes without making any assumption on the central parts of demand distribution and to predict beyond the range of available data. While applied on individual loads, the techniques described in this book can be extended naturally to substations, or to commercial settings. Extreme value theory techniques presented can be also used across other disciplines, for example for predicting heavy rainfalls, wind speed, solar radiation and extreme weather events. The book is intended for students, academics, engineers and professionals that are interested in short term load prediction, energy data analytics, battery control, demand side response and data science in general.</p